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Full-Text Articles in Other Computer Sciences
Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead
Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead
Engineering Faculty Articles and Research
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Zhongmei Yao
Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …
Context Aware Privacy Preserving Clustering And Classification, Nirmal Thapa
Context Aware Privacy Preserving Clustering And Classification, Nirmal Thapa
Theses and Dissertations--Computer Science
Data are valuable assets to any organizations or individuals. Data are sources of useful information which is a big part of decision making. All sectors have potential to benefit from having information. Commerce, health, and research are some of the fields that have benefited from data. On the other hand, the availability of the data makes it easy for anyone to exploit the data, which in many cases are private confidential data. It is necessary to preserve the confidentiality of the data. We study two categories of privacy: Data Value Hiding and Data Pattern Hiding. Privacy is a huge concern …
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Computer Science Faculty Publications
Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …